Update utils.py to contain the correct buttons

#5
Files changed (1) hide show
  1. src/display/utils.py +1 -26
src/display/utils.py CHANGED
@@ -26,7 +26,7 @@ auto_eval_column_dict = []
26
  auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
27
  auto_eval_column_dict.append(["model", ColumnContent, ColumnContent("Model", "markdown", True, never_hidden=True)])
28
  #Scores
29
- auto_eval_column_dict.append(["average", ColumnContent, ColumnContent("Average ⬆️", "number", True)])
30
  for task in Tasks:
31
  auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "number", True)])
32
  # Model information
@@ -91,10 +91,6 @@ class WeightType(Enum):
91
  class Precision(Enum):
92
  float16 = ModelDetails("float16")
93
  bfloat16 = ModelDetails("bfloat16")
94
- float32 = ModelDetails("float32")
95
- #qt_8bit = ModelDetails("8bit")
96
- #qt_4bit = ModelDetails("4bit")
97
- #qt_GPTQ = ModelDetails("GPTQ")
98
  Unknown = ModelDetails("?")
99
 
100
  def from_str(precision):
@@ -102,34 +98,13 @@ class Precision(Enum):
102
  return Precision.float16
103
  if precision in ["torch.bfloat16", "bfloat16"]:
104
  return Precision.bfloat16
105
- if precision in ["float32"]:
106
- return Precision.float32
107
- #if precision in ["8bit"]:
108
- # return Precision.qt_8bit
109
- #if precision in ["4bit"]:
110
- # return Precision.qt_4bit
111
- #if precision in ["GPTQ", "None"]:
112
- # return Precision.qt_GPTQ
113
  return Precision.Unknown
114
 
115
  # Column selection
116
  COLS = [c.name for c in fields(AutoEvalColumn) if not c.hidden]
117
- TYPES = [c.type for c in fields(AutoEvalColumn) if not c.hidden]
118
- COLS_LITE = [c.name for c in fields(AutoEvalColumn) if c.displayed_by_default and not c.hidden]
119
- TYPES_LITE = [c.type for c in fields(AutoEvalColumn) if c.displayed_by_default and not c.hidden]
120
 
121
  EVAL_COLS = [c.name for c in fields(EvalQueueColumn)]
122
  EVAL_TYPES = [c.type for c in fields(EvalQueueColumn)]
123
 
124
  BENCHMARK_COLS = [t.value.col_name for t in Tasks]
125
 
126
- NUMERIC_INTERVALS = {
127
- "?": pd.Interval(-1, 0, closed="right"),
128
- "~1.5": pd.Interval(0, 2, closed="right"),
129
- "~3": pd.Interval(2, 4, closed="right"),
130
- "~7": pd.Interval(4, 9, closed="right"),
131
- "~13": pd.Interval(9, 20, closed="right"),
132
- "~35": pd.Interval(20, 45, closed="right"),
133
- "~60": pd.Interval(45, 70, closed="right"),
134
- "70+": pd.Interval(70, 10000, closed="right"),
135
- }
 
26
  auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
27
  auto_eval_column_dict.append(["model", ColumnContent, ColumnContent("Model", "markdown", True, never_hidden=True)])
28
  #Scores
29
+ auto_eval_column_dict.append(["average", ColumnContent, ColumnContent("Rank", "number", True)])
30
  for task in Tasks:
31
  auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "number", True)])
32
  # Model information
 
91
  class Precision(Enum):
92
  float16 = ModelDetails("float16")
93
  bfloat16 = ModelDetails("bfloat16")
 
 
 
 
94
  Unknown = ModelDetails("?")
95
 
96
  def from_str(precision):
 
98
  return Precision.float16
99
  if precision in ["torch.bfloat16", "bfloat16"]:
100
  return Precision.bfloat16
 
 
 
 
 
 
 
 
101
  return Precision.Unknown
102
 
103
  # Column selection
104
  COLS = [c.name for c in fields(AutoEvalColumn) if not c.hidden]
 
 
 
105
 
106
  EVAL_COLS = [c.name for c in fields(EvalQueueColumn)]
107
  EVAL_TYPES = [c.type for c in fields(EvalQueueColumn)]
108
 
109
  BENCHMARK_COLS = [t.value.col_name for t in Tasks]
110